WAVELET ANALYSIS OF EEG SIGNALS DURING MOTOR IMAGERY

被引：0
|
作者：
Yamaguchi, Tomonari [1 ]
Fujio, Mitsuhiko [1 ]
Inoue, Katsuhiro [1 ]
Pfurtscheller, Gert [2 ]
机构：
[1] Kyushu Inst Technol, Iizuka, Fukuoka, Japan
[2] Graz Univ Technol, A-8010 Graz, Austria
来源：
PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON WAVELET ANALYSIS AND PATTERN RECOGNITION, VOLS 1 AND 2 | 2008年
关键词：
EEG; BCI; ERS; ERD; Motor imagery; Multiresolution analysis; Mathematical morphology; Intertrial variance;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
ERS and ERD (event-related synchronization and desynchronization) are observed in EEG (electroencephalogram) signals around such events as sensitive stimulus, motions, cognitive actions etc. Usually, ERS/ERD features of EEG are extracted as variances of band-passed signals of several trials. To make use of these features to recognize inputs for BCI (brain-computer interface), we applied discrete wavelet analysis to extraction of ERS/ERD features from a small number of EEG signals during motor imagery. We employed Daubechies, convolution and spline biorthogonal mothers for linear wavelet analysis, also Haar type structural function for morphological wavelet analysis. Then our extraction method was estimated by the pattern recognition based on AR model.
引用
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页码：454 / +
页数：2
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